Open research information to inform regional policies: the case of Tuscany Region

The Region of Tuscany supports research and innovation activities in its territory through direct R&D funding and through facilitation and coordination actions between the different actors of the regional ecosystem. In order to better inform and support its policies, the Tuscany Region has set up a regional research observatory, which integrates various sources of data and combine metadata on R&D activities, funding and human resources. In this context, the Region has committed to identifying, analysing and integrating open research information into its Observatory, deciding to abandon the use of proprietary research information (in particular for scientific publications) in favour of fully open data sources. In the same view, an internal action has also been launched (in collaboration with various regional government offices) to improve the publication of and access to metadata on research funding. The Tuscany experience is an opportunity to demonstrate the potential and opportunities of open research information to support public policies and to facilitate a better dialogue with regional and national stakeholders, from regional universities to the national evaluation agencies. However, it also shows the challenge faced by public administrations that are too often organised ina ”silos” structure, which is not optimal to deal with transversal challenges, as research should be.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-07
DOI
https://doi.org/10.5281/zenodo.13899950
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Open research information to inform regional policies: the case of Tuscany Region

Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

Open research information to inform regional policies: the case of Tuscany Region

article en

Abstract

The Region of Tuscany supports research and innovation activities in its territory through direct R&D funding and through facilitation and coordination actions between the different actors of the regional ecosystem. In order to better inform and support its policies, the Tuscany Region has set up a regional research observatory, which integrates various sources of data and combine metadata on R&D activities, funding and human resources. In this context, the Region has committed to identifying, analysing and integrating open research information into its Observatory, deciding to abandon the use of proprietary research information (in particular for scientific publications) in favour of fully open data sources. In the same view, an internal action has also been launched (in collaboration with various regional government offices) to improve the publication of and access to metadata on research funding. The Tuscany experience is an opportunity to demonstrate the potential and opportunities of open research information to support public policies and to facilitate a better dialogue with regional and national stakeholders, from regional universities to the national evaluation agencies. However, it also shows the challenge faced by public administrations that are too often organised ina ”silos” structure, which is not optimal to deal with transversal challenges, as research should be.

Zenodo (CERN European Organization for Nuclear Research)
Regione Toscana
Industry, innovation and infrastructure
Openalex Percentile: Top 37%
Research Data Management Practices
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.